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beit-base-patch16-224-pt22k-ft22k-finetuned-conspiracy_imagery – AI Model by rvchi-schwenn | AlphaNeural AI
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beit-base-patch16-224-pt22k-ft22k-finetuned-conspiracy_imagery
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tensorboard
safetensors
beit
generated_from_trainer
microsoft/beit-base-patch16-224-pt22k-ft22k
finetune
apache-2.0
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beit-base-patch16-224-pt22k-ft22k-finetuned-conspiracy_imagery
This model is a fine-tuned version of
microsoft/beit-base-patch16-224-pt22k-ft22k
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.0016
Accuracy: 0.6898
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 6
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.8993
0.9630
13
1.3949
0.4259
1.4291
2.0
27
1.1265
0.6204
1.0122
2.9630
40
1.1280
0.6065
0.8817
4.0
54
1.0542
0.6389
0.8138
4.9630
67
1.0016
0.6898
0.779
5.7778
78
0.9987
0.6806
Framework versions
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
